What AI Visibility Toolkit scans
Toolkit starts with crawl reality. It checks whether important pages are reachable, whether robots.txt or noindex rules block retrieval, whether HTML is readable without heavy rendering, and whether canonical and JSON-LD signals are present.
Then it scores citation readiness: are your pages structured in a way that answer engines can extract a definition, steps, pricing context, FAQs, and support evidence from?
- robots.txt and sitemap access
- Readable HTML vs JS-heavy rendering risk
- Canonical and JSON-LD coverage
- Snippet-readiness across core pages
- Generated llms.txt based on scanned important pages
What it gives you back
Output is designed for action, not vague GEO theater.
- Indexability score and AI citation readiness score
- Issue list ranked by severity with fix guidance
- Snippet-readiness view for definition, steps, pricing, and FAQ gaps
- Generated llms.txt file ready to publish at root
- Next-best-action recommendations tied to scanned evidence
Why this is useful
Most teams talking about agent SEO skip straight to prompts and citations. That is upside-down. If AI fetchers cannot access or cleanly read key pages, later citation work is weak by default.
Toolkit enforces better order: make pages accessible, then extractable, then citable.
What it does not claim
It does not claim guaranteed visibility in ChatGPT, Claude, Gemini, or Perplexity.
It does not invent hidden traffic numbers or “AI rankings.” It focuses on auditable signals and labels missing evidence clearly.
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Frequently asked questions
Does this replace normal SEO?
No. It extends normal SEO into answer-engine readiness by checking access, structure, and citation support signals.
Does the toolkit create llms.txt for me?
Yes. It generates an llms.txt draft from the pages it scans so you can publish it at your site root.
Can it see blocked or protected sites?
Yes, when Scan Access is configured. It uses the same owned-site crawl allow header flow as other protected scans in UpSearch.